Molecular mechanisms of encoding and decoding information in cell computing.

The process of computing may be defined simply as the goal-directed selection process (GDSP) that selects m out of n possible choices to achieve some desired goals, thereby generating or utilizing the amount of Shannon information, I, that can be approximated as I = - log2 (m/n) bits. There are at least 3 distinct kinds of the physicochemical systems that can execute GDSP; (i) enzymes (i.e., microscopic or molecular computers), (ii) living cells (as mesoscopic computers), and (iii) brains (as macroscopic computers). In order to help define the principles and mechanisms underlying cell computing, it was thought necessary to compare cell computers with molecular computers (e.g., enzymes) on the one hand and with the macroscopic computers (e.g., Turing machine) on the other. It was concluded that all these different kinds of computers are ultimately driven by the information-energy particle called gnergons, consistent with the Gnergy Principle of Organization formulated by the present auditor in 2018. Also, it was concluded that to delineate how cells compute supported by enzymes necessitated treating enzymes not only as particles but also as standing waves, thus leading to the postulate of the wave-particle duality of enzymes formulated in this paper for the first time, in analogy to the wave-particle duality of light formulated in physics about 100 years ago.

Fundamental, Quantitative Traits of the "Sociotype".

In whatever domain of life, from cells to organisms to societies, communicative exchanges underlie the formation and maintenance, and decay, of the emerging collective structures. It can be clearly seen in the human social world. The different classes of social bonds in a complex society revolve around, and are intimately related with, the communicative relationships that every individual entertains-essentially via face-to-face conversation. In the present work we have investigated the fundamental metrics of both social bonds and communicative exchanges along the development of the "sociotype" construct. It is a new approach developed by the authors within the genotype-phenotype-sociotype conceptual triad. The sociotype means the relative constancy, or better the similar fabric, of the social world in which each individual life is developed. In order to ascertain the metrics of the fundamental quantitative traits inherent in the sociotype, a fieldwork involving a total of 1475 individuals (68.59% female, and 49.79 mean age, SD = 21.47) was carried out. The four relational realms of family, friends, work/study, and acquaintances were investigated. The overall results about conversation time (an average of 220 min/day), and about the number of social bonds (an average of 98), differ from previous assumptions, such as Dunbar's number or Killworth's number. Other results about gender, age, and use of social media and Internet contribute to highlight significant differences among the different social segments, and particularly the diminished "sociotype" of the elderly. Finally, it is curious that a non-Gaussian distribution has been obtained for the specific population allotment of these metrics, and intriguingly the Planckian distribution equation (PDE) appears to be a most cogent fit.

Conformon-driven biopolymer shape changes in cell modeling.

Conceptual models of the atom preceded the mathematical model of the hydrogen atom in physics in the second decade of the 20th century. The computer modeling of the living cell in the 21st century may follow a similar course of development. A conceptual model of the cell called the Bhopalator was formulated in the mid-1980s, along with its twin theories known as the conformon theory of molecular machines and the cell language theory of biopolymer interactions [Ann. N.Y. Acad. Sci. 227 (1974) 211; BioSystems 44 (1997) 17; Ann. N.Y. Acad. Sci. 870 (1999a) 411; BioSystems 54 (2000) 107; Semiotica 138 (1-4) (2002a) 15; Fundamenta Informaticae 49 (2002b) 147]. The conformon theory accounts for the reversible actions of individual biopolymers coupled to irreversible chemical reactions, while the cell language theory provides a theoretical framework for understanding the complex networks of dynamic interactions among biopolymers in the cell. These two theories are reviewed and further elaborated for the benefit of both computational biologists and computer scientists who are interested in modeling the living cell and its functions. One of the critical components of the mechanisms of cell communication and cell computing has been postulated to be space- and time-organized teleonomic (i.e. goal-directed) shape changes of biopolymers that are driven by exergonic (free energy-releasing) chemical reactions. The generalized Franck-Condon principle is suggested to be essential in resolving the apparent paradox arising when one attempts to couple endergonic (free energy-requiring) biopolymer shape changes to the exergonic chemical reactions that are catalyzed by biopolymer shape changes themselves. Conformons, defined as sequence-specific mechanical strains of biopolymers first invoked three decades ago to account for energy coupling in mitochondria, have been identified as shape changers, the agents that cause shape changes in biopolymers. Given a set of space- and time-organized teleonomic shape changes of biopolymers driven by conformons, all of the functions of the cell can be accounted for in molecular terms-at least in principle. To convert a conceptual model of the cell into a computer model, it is necessary to represent the conceptual model in an algebraic language. To this end, we have begun to apply the process algebra of Milner [Communicating and Mobile Systems: The pi-calculus, Cambridge University Press, Cambridge, 1999] to develop what is here called the "shape algebra," capable of describing complex and mobile patterns of interactions among biomolecules leading to cell functions.